Bioenergetic mapping of ‘healthy microbiomes’ via compound processing potential imprinted in gut and soil metagenomes
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Abstract
Despite mounting evidence of their importance in human health and ecosystem functioning, the definition and measurement of ‘healthy microbiomes’ remain unclear. More advanced knowledge exists on health associations for compounds used or produced by microbes. Environmental microbiome exposures (especially via soils) also help shape, and may supplement, the functional capacity of human microbiomes. Given the synchronous interaction between microbes, their feedstocks, and micro-environments, with functional genes facilitating chemical transformations, there exists an intriguing opportunity to examine microbiomes in terms of their capacity to process compounds relevant to human health. Here we integrate functional genomics and biochemistry frameworks to derive new quantitative measures of the potential for human gut and environmental soil metagenomes to process major compound classes (e.g., lipids, carbohydrates) and selected biomolecules (e.g., vitamins, short-chain fatty acids) linked to human health. Metagenome functional potential profile data were translated into a universal compound mapping ‘landscape’ based on bioenergetic van Krevelen mapping of function-level meta-compounds and corresponding functional relative abundances, reflecting imprinted genetic capacity of microbiomes to metabolize an array of different compounds. We show that measures of ‘compound processing potential’ associated with human health and disease (examining atherosclerotic cardiovascular disease, colorectal cancer, type 2 diabetes and anxious-depressive behavior case studies), and displayed seemingly predictable shifts along gradients of ecological disturbance in plant-soil ecosystems (three case studies). Ecosystem quality explained 60–92% of variation in soil metagenome compound processing potential measures in a post-mining restoration case study dataset. With growing knowledge of the varying proficiency of environmental microbiota to process human health associated compounds, we might design environmental interventions or nature prescriptions to modulate our exposures, thereby advancing microbiota-oriented approaches to human health. Compound processing potential offers a simplified, integrative approach for applying metagenomics in ongoing efforts to understand and quantify the role and linkages of microbiota in environmental- and human-health.
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Functional potential profiles were derived from good quality read 1 sequences using SUPER-FOCUS570(33) software, linked to the Diamond sequence aligner (v0.9.19; 90) and version 2 100% identity-571clustered reference database (100_v2; https://github.com/metageni/SUPER-FOCUS/issues/66).572Where subjects/samples were represented by multiple sequence files, the combined SUPER-FOCUS573outputs were normalized so that the total functional relative abundances summed to 100% in each574subject/sample
I'm really excited by the approach profiled in this paper. I think it's a very clever use of chemical reactions and stoichiometry. However, I'm concerned about the pre-processing step mentioned here. Do you have a sense of how lossy SUPER-FOCUS is, especially for soil microbiomes? Typically, metagenome analysis of soils can lose up to 80% of …
Functional potential profiles were derived from good quality read 1 sequences using SUPER-FOCUS570(33) software, linked to the Diamond sequence aligner (v0.9.19; 90) and version 2 100% identity-571clustered reference database (100_v2; https://github.com/metageni/SUPER-FOCUS/issues/66).572Where subjects/samples were represented by multiple sequence files, the combined SUPER-FOCUS573outputs were normalized so that the total functional relative abundances summed to 100% in each574subject/sample
I'm really excited by the approach profiled in this paper. I think it's a very clever use of chemical reactions and stoichiometry. However, I'm concerned about the pre-processing step mentioned here. Do you have a sense of how lossy SUPER-FOCUS is, especially for soil microbiomes? Typically, metagenome analysis of soils can lose up to 80% of information due to the system complexity and the amount we have yet to observe. Depending on the fraction of loss of functional information, how do you expect that to impact that results presented in this study?
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